Two-dimensional magnetotelluric data inversion using Lanczos bidiagonalization method with active constraint balancing

Abstract

The magnetotelluric (MT) technique is an electromagnetic geophysical method, which is widely used as a complementary to seismic surveys for exploration of hydrocarbon reservoirs. In the inversion process, the method of matrix inverse calculation has a considerable effect on the speed of the inversion and the quality of obtained models. Lanczos Bidiagonalization (LB) method has been reported to be a fast and efficient approach for solving the inversion problems. In this study, we employ LB method for inverting large-scale 2D MT data. In LB algorithm, the full set of equations is replaced by a dimensionally reduced system of equations. As a result, the speed of the solution procedure is increased, while the original problem is solved with a high accuracy. In addition, we employ active constraint balancing approach for determining the optimum regularization parameter. The advantage of the method is that for highly resolvable parameters, a small value of the Lagrangian multiplier is assigned, and vice versa. The results of the synthetic data inversion show that both methods require equal computer memory but LB method is faster and more reliable than conjugate gradient method. The proposed approach is also applied to inverse real MT data collected from the Kashan area. The Kashan area is the most interesting area for oil and gas exploration of the Central Iran Basin. The inversion results obtained by LB are in a good agreement with the geological structure of the study area and the drilling data.